Information needs and perceptions of chatbots for hypertension medication self-management: a mixed methods study

Abstract

Objective Chatbots have potential to deliver interactive self-management interventions but have rarely been studied in the context of hypertension or medication adherence. The objective of this study was to better understand patient information needs and perceptions of chatbots to support hypertension medication self-management. Materials and Methods Mixed methods were used to assess self-management needs and preferences for using chatbots. We purposively sampled adults with hypertension who were prescribed at least one medication. Participants completed questionnaires on sociodemographics, health literacy, self-efficacy, and technology use. Semi-structured interviews were conducted, audio-recorded, and transcribed verbatim. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using applied thematic analysis. Results Thematic saturation was met after interviewing 15 participants. Analysis revealed curiosity toward chatbots, and most perceived them as humanlike. The majority were interested in using a chatbot to help manage medications, refills, communicate with care teams, and for accountability toward self-care tasks. Despite general enthusiasm, there were concerns with chatbots providing too much information, making demands for lifestyle changes, invading privacy, and usability issues with deployment on smartphones. Those with overall positive perceptions toward chatbots were younger and taking fewer medications. Discussion Chatbot-related informational needs were consistent with existing self-management research, and many felt chatbots would be valuable if customizable and compatible with patient portals, pharmacies, or health apps. Conclusion Although most were not familiar with chatbots, patients were interested in interacting with them, but this varied. This research informs future design and functionalities of conversational interfaces to support hypertension self-management.

Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review

“…Age, IT skills, preference for talking to computers, perceived utility, positive attitude, and perceived trustworthiness were found to be associated with AI acceptability [25,26]. Australia and New Zealand [35] 4 (15) Canada [27,[36][37][38] 6 (23) China [22,32,33,39,40] 1 (4) France [41] 2 (8) India [24,42] 1 (4) Korea [48] 1 (4) Saudi Arabia [29] 1 (4) Switzerland [30] 5 (19) United Kingdom [23,26,31,43,44] 1 (4) United Kingdom, Cyprus, Australia, the Netherlands, Sweden, Spain, United States, and Canada [28] 3 (12) United States [25,45,46] Type of publication 24 (92) Journal papers [22][23][24][25][26][27][28][29][31][32][33][34][35][36][37]…”

“…All the studies showed at least moderate acceptability, or >50% of the participants showed acceptance toward the use of AI in health care, albeit only for minor conditions [ 26 ]. Age, IT skills, preference for talking to computers, perceived utility, positive attitude, and perceived trustworthiness were found to be associated with AI acceptability [ 25 , 26 ].…”

“…Overall, 15% (4/26) of studies described the need to improve user experience to increase user engagement with AI [ 23 , 25 , 28 , 31 ]. Strategies include needs-based interaction timing, the use of suitable verbal and nonverbal expressions, interconnectedness with other information sources (eg, electronic health record), apps (eg, calendar), and devices (eg, smart home technology–enabled devices).…”

“…Sample sizes for studies with human subject responses ranged from 11 to 2780, and secondary data (ie, journal articles and app reviews) ranged from 31 to 1826 [22][23][24]. Interestingly, 19% (5/26) of studies focused on the use of chatbots in health care [23][24][25][26][27] and 31% (8/26) of studies measured acceptability using questionnaires, surveys, interviews [25,26,[28][29][30][31][32][33], and the discrete choice experiment (Multimedia Appendix 4 [22][23][24][25][26][27][28][29][30][31][32]34,36,37,39,[41][42][43][44]47]) [34]. All the studies showed at least moderate acceptability, or >50% of the participants showed acceptance toward the use of AI in health care, albeit only for minor conditions [26].…”

“…Several positive perceptions on the use of AI in health care were highlighted in our findings (Table 2). [43] worried AI will replace their job believed there may be serious privacy issues could be useful or extremely useful in their field of work NS NS Patients were unsure whether Patients were not concerned NS NS NS Easton et al [31] to treat a chat-over data sharing bot as a real physician or an adviser Less than half of the social NS Social media users were pes-Distrust of AI companies ac-NS NS NS Gao et al [22] media posts ex-simistic about counted for a pressed that AI the immaturity quarter of all would complete-of AI technology negative opinions among social media users ly or partially replace human doctors NS NS There were concerns with chat-There were concerns with chat-NS The majority were interested in using a NS Griffin et al [25] bots…”